Integrated population models (IPMs) represent the powerful combination, in a single Leslie-type of model, of different data sources that are informative about the dynamics of an animal population (Besbeas et al. 2002; Schaub et al. 2007). Typical IPMs combine one or more time-series of counts with another data set that is directly informative about survival probabilities, such as ring-recovery or capture-recapture. However, many other sources of demographic information may be envisioned instead or in addition, including age-at-death data, occupancy or replicated point count data. Currently, for non-statisticians the only practical manner to develop and fit an IPM is using BUGS software (WinBUGS, OpenBUGS, JAGS).

This course is a practical and hands-on introduction to developing and fitting integrated population models using BUGS software. It is based on the successful book by Kéry & Schaub, Bayesian Population Analysis using WinBUGS (Academic Press, 2012), which will be handed out as part of the course.Beyond IPMs, the course also provides an in-depth introduction for ecologists and wildlife managers to a very wide variety of models fit using BUGS software and as documented in the BPA book.Contents include the following topics:Basic introduction: • Hierarchical models as an overarching theme of population modeling, including IPMs• Bayesian analysis of hierarchical models• Introduction to BUGS software in the context of generalised linear models (GLM) and traditional random-effects modelsIngredients of Integrated Population Models:• State-space models• Cormack-Jolly-Seber models for estimating survival probabilities• Multistate capture-recapture models for estimating survival and transition probabilitiesIntegrated Population Models:• Introduction to matrix population models and their analysis with BUGS• Theory of integrated population models• Various case studies which differ in complexity and in the data types that are combined

In this intermediate-level workshop about 3/4 of the time are spent on lecturing and 1/4 on solving exercises. No previous experience with BUGS software, or Bayesian statistics, is assumed. However, a good working knowledge of modern regression methods (ANOVA, ANCOVA, GLMs) and of program R is required. Moreover, a basic understanding of capture-recapture and/or occupancy models is desirable.Send your application to Michael Schaub (michael.schaub@vogelwarte.ch), with CC to Marc Kéry (marc.kery@vogelwarte.ch) and David Koons (david.koons@usu.edu) describing your background and knowledge in statistical modeling, R and WinBUGS/OpenBUGS/JAGS and capture-recapture, by 31 March 2016 at the latest. Workshop invitations will be sent out immediately afterwards.